Image Context Based Similarity Retrieval System

Arpana D. Mahajan and Sanjay Chaudhary
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Arpana D. Mahajan: Madhav University
Sanjay Chaudhary: Madhav University

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 73-80 from Springer

Abstract: Abstract The rapid development in multimedia and imaging technology, the numbers of images uploaded and shared on the internet have increased. It leads to develop the highly effective image retrieval system to satisfy the human needs. The content-text image retrieval (CTIR) system which retrieves the image based on the high level features such as tags which are not sufficient to describe the user’s low level perception for images. Therefore reducing this semantic gap problem of image retrieval is challenging task. Some of the most important notions in image retrieval are keywords, terms or concepts. Terms are used by humans to describe their information need and it also used by system as a way to represent images. Here in this paper different types of features their advantage and disadvantages are described.

Keywords: Context retrieval; High level features; Distances; WordNet; Flickr; CISS (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_7

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DOI: 10.1007/978-3-030-41862-5_7

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